Analysis of Electromyography Signals for Control of Mechanical Prosthesis using Machine Learning Techniques-Reference-Cited by-同舟云学术

Analysis of Electromyography Signals for Control of Mechanical Prosthesis using Machine Learning Techniques

Published:2024-01-04 Issue: Volume:101 Page:1059-1067
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Container-title:2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)
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Author:

M Kanipriya¹,Sugumaran D.²,Pandiyarajan V.³,B S Yogananda⁴,Selvakumar P.⁵,S Mohan⁶

Affiliation:

1. SRM Institute of Science and Technology,Department of Computational Intelligence,Chennai,Tamil Nadu,India,603203

2. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology,Department of Information Technology,Chennai,Tamil Nadu,India,600062

3. Sri Sairam College of Engineering,Department of Mechanical Engineering,Bengaluru,Karnataka,India,562106

4. Department of Mechanical Engineering, Sri Sairam College of Engineering, Bengaluru, India

5. Department of Chemistry Nehru Institute of technology Coimbatore,Tamilnadu,India

6. Nehru Institute of Engineering and Technology,Department of Electronics and Communication Engineering,Coimbatore,Tamil Nadu,India,641105

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10467178/10467214/10467707.pdf?arnumber=10467707

Reference15 articles.

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3. “Detection and evaluation of lung cancer in CT scan images using two convolutional neural network architectures”;Sebastian;Journal of the Balkan Tribological Association,2023

4. Practice-Effects in Performance-Based Balance Tests Limit Their Application Among Lower-Limb Prosthesis Users

5. Research on ship intelligent manufacturing data monitoring and quality control system based on industrial Internet of Things